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Effects of 1-MCP on tomato fruit ripening have been well studied, but much less attention has been given to its effects on vine quality. In a series of experiments, 0.5 or 1 µL L-1 1-MCP was applied to tomato clusters when the least mature fruit on the vine was mature green (MG), breaker (BR) or light red (LR). The clusters were stored at 12oC for 18 days. Overall fruit quality remained high in the MG, BR and LR fruit clusters for 18, 9, and 6 days, respectively. Quality of the 1-MCP-treated BR stage fruit did not decline until after 12 days, while little effect of 1-MCP was found for the LR fruit. Cluster weight was not affected by 1-MCP treatment. However, visual appearance of the vine tissues was greatly affected by 1-MCP. Loss of vine quality was lowest in the MG vines without 1-MCP treatment. However, the highest quality ratings were found in 1-MCP treated vines, regardless of fruit maturity. Retention of vine quality by 1-MCP was closely associated with reduced water loss from the vine tissues. These results confirm that 1-MCP can delay ripening of tomato fruit, but also highlight that the benefits of 1-MCP may be through better visual appearance of the cluster vines.

Fresh produce quality is a critical determinant of consumer preference and market value, with high-quality tomatoes often fetching premium prices. Traditional quality assessment methods, though effective, are typically labor-intensive, destructive, and impractical for real-time monitoring. In this study, we explore the potential of low-cost ($0.99 per unit) metal oxide semiconductor (MOS) gas sensors—MQ series (MQ2, MQ5, MQ6, MQ7, MQ9, and MQ135)—as a rapid, non-destructive, and cost-efficient tool for distinguishing high-quality tomatoes based on their cultivation in nitrogen-rich or nitrogen-deficient soils. Organic tomatoes, harvested from plants exposed to relatively high (High-N) and relatively low (Low-N) levels of bioavailable nitrogen (N) were enclosed in airtight containers equipped with MQ sensors to capture their volatile organic compound (VOC) emissions over 48 hours. Three replicates were used for each N level. Complementary laboratory-based quality assessments measured fresh weight, soluble sugar content, titratable acidity, pH, firmness, color space (Lab*), antioxidant capacity (DPPH assay), and total phenolic content. Gas chromatography-mass spectrometry (GC-MS) was utilized for VOC profiling. The resulting sensor and analytical data were preprocessed and normalized, followed by training 193 machine learning models with principal component analysis (PCA) at a 95% variance threshold in MATLAB. Significant differences were observed between High-N and Low-N treatments across several quality parameters. High-N tomatoes exhibited a 25.32% increase in average fruit fresh weight (p = 0.002), whereas Low-N tomatoes had 18.80% higher firmness (p = 0.020). Low-N tomatoes showed a 27.09% increase in antioxidant capacity (p = 0.0001), a possible indication of an adaptive response to N deficiency. Whereas VOC analysis revealed higher concentrations of octanoic acid, nonanoic acid, and 2-methyl-1-propanol in High-N tomatoes, with increases of 142.67%, 191.46%, and 37.72%, respectively, compared to Low-N tomatoes (p = 0.007, p = 0.020, p = 0.040). Sensor performance analysis demonstrated that MQ9 and MQ5 sensors were the most effective in differentiating between the two nitrogen treatments, with ensemble learning, neural networks, and support vector machines achieving 100% classification accuracy, followed by MQ135 and MQ2. Feature reduction criterion identified a minimal yet highly discriminative subset—including MQ9 sensor responses, octanoic acid, 4-heptanone, nonanoic acid, 1-penten-3-ol, 2-methyl-1-propanol, limonene, 3-methylbutanoic acid, 2-heptanone, fresh weight, and DPPH values—yielding classification accuracies of 97.06% during training and 89.29% in testing with a tri-layer neural network model. These findings underscore the potential of low-cost MOS gas sensors, particularly MQ9, as a viable, non-destructive alternative for real-time quality assessment of tomatoes.

Carotenoids are natural pigments that give fruits and vegetables their yellow, orange, and red colors, and their consumption is associated with numerous health benefits. Most carotenoids occur in isomeric forms (primarily cis and trans); this poses challenges for efficient separation and identification during chromatographic analysis. Tomato (Solanum lycopersicum), an economically important crop, has high nutritional and health benefits, attributed mainly to carotenoids. Lycopene, a major carotenoid in tomatoes, predominantly exists in the trans isoform; however, the trans isoform is less bioavailable than the cis isoform. To accurately measure these isoforms in tomatoes and thus provide information for breeding tomatoes with more cis lycopene, we aimed to develop an Ultra-High Performance Liquid Chromatography (UHPLC) method based on mobile phase (MP) modifiers to measure a wide range of carotenoids (cis and trans) across different tomato varieties (heirloom and cherry) with different colors (green, yellow, orange, purple, and red). The chromatographic parameters, such as temperature (15-30 °C), flow rate (0.3-1.5 ml/min), column lengths (50, 150, and 250 mm), and gradients, and MP modifiers (water, acetonitrile, tetrahydrofuran, triethylamine, ammonium acetate, and ethyl acetate) were optimized. Among the tested parameters, methanol and tert-butyl methyl ether as MP, including ethyl acetate (10%) as a modifier, and C30 column (150 x 4.6 mm) at 20 °C gave the best resolution, allowing the separation of up to 20 peaks indicating individual compounds and isoforms in 35 min. The optimized UHPLC method was also validated for complete profiling, recovery, precision, limit of detection, and quantification. The complexity of the profile based on the number of peaks followed the following order: Orange Heirloom (15) > Orange Cherry (15), Red Cherry (15) > Red Heirloom (13) > Green Heirloom (13) > Purple Cherry (13) > Yellow Cherry (2). Among all the tested tomatoes, trans-lycopene, 5-cis-lycopene, and β-carotene were the predominant carotenoids, followed by 9- and 13-cis-lycopene, and for the first time, mutatoxanthin was detected in Orange Heirloom tomatoes. This method provided efficient peak separation resolution, although not all of them were identified as potential carotenoids; however, their identification could be confirmed by mass spectrometry analysis in future studies. The efficiency, separation, and quantification in this method make it robust for carotenoid analysis in any tomato variety regardless of color. USDA-NIFA-2024-51181-43464 supported this work through the Vegetable and Fruit Improvement Center and partially funded by the Texas A

Tomato metabolism changes in response to environmental conditions such as heat, drought, and soil salinity. This response causes changes in amino acid levels, which are directly related to enzyme activity, photosynthesis, and stress responses. For example, measuring the increase of proline during drought is a biomarker for stress conditions. Qualitative and quantitative analysis of amino acid levels requires precise chromatographic conditions in controlled settings. To accomplish consistent amino acid separation, individual chemical groups require adjustments to chromatographic parameters such as mobile phase composition, pH levels, column type and size, temperature, absorbance/emission wavelength, and gradient combination. This study developed a precise ultra-high performance liquid chromatography (UPLC) approach with a fluorescence detector (FLD) to quantify various amino acids, including γ-aminobutyric acid (GABA), using optimized concentrations of a weak acid (formic acid) and weak base (triethylamine) as modifiers in water and acetonitrile mobile phases, respectively. Buffers are commonly employed in amino acid chromatography; however, excessive usage can result in precipitation and salt accumulation, blocking the pumps. They may also cause pH shifts under high pressure and temperature conditions. Optimized chromatographic conditions improve amino acid separation and quantification. A mobile phase of 0.2% formic acid in water (A) and triethylamine in acetonitrile (B) produced the best results, with maximal separation at 55°C. The gradient began at 90% A and gradually decreased until minute 20, when it returned to the beginning conditions. The injection volume remained steady at 5 µL, with FLD detection peaking at 360 nm. Distinct peaks formed at a 1.0 mL/min flow rate while the pressure was maintained at 1300 psi. Calibration R² results were between 0.97 and 1.0, indicating technique correctness. Separation of real samples found 18 chemicals with retention time changes ranging from 0.01 to 0.05 min. Tomato fruit samples were procured from two developmental stages and amino acid levels were measured. This will provide a benchmark for distinguishing the tomato varieties based on their stress-resilient behavior. This work was partially supported by USDA-NIFA-2024-51181-43464, USDA-NIFA-AFRI 2023-67013-39616 through the Vegetable and Fruit Improvement Center and Institute for Advancing Health Through Agriculture of the Texas A

Large-canopy training systems commonly used in Washington pear orchards create sunlight exposure disparities among fruits. Pear ripening is influenced by sunlight exposure and variability contributes to non-uniform ripening postharvest outcomes. To enhance uniformity in fruit batches based on sunlight exposure, d ‘Anjou pears were sorted according to a newly adapted Chlorophyll-carotenoid index (Cri) based on Hyperspectral images. In September 2024, d’Anjou pears were harvested in three commercial orchards located across distinct growing regions in Washington and Oregon. Reflectance spectral information for each fruit was extracted from Hyperspectral images, and wavebands related to Chlorophyll and carotenoids (430, 662, 454, 549 nm) were subsequently used to calculate Cri values for each fruit. This index value allowed for sorting of fruit into batches under three sunlight categories: Low, Medium, and High. Fruit was kept in controlled atmosphere storage (3.0 % O2, 0.8 % CO2, 0 oC) and quality (Chlorophyll degradation (IAD), firmness (lb)), was studied after 4 months of storage plus 7 days at room temperature (20 oC). Fruit maturity indexes, at harvest, showed no differences between fruit categories. Chlorophyll degradation (IAD) on fruit surface showed that in two of the three orchards, low-exposure fruits exhibited lower values in comparison to high-exposure ones (P ≤ 0.01). Firmness values were significantly lower in high-exposure categories after cold storage and room temperature periods, landing at around 12 lbs and 3 lbs, respectively (P ≤ 0.01). No major differences in physiological disorders incidence between sunlight categories were observed. Further investigation needs to be conducted to determine how these categories behave in longer cold-chain storage scenarios.

In Washington state, pears are typically cultivated on trees with large canopies, which results in different levels of sun exposure and, therefore, fruit maturity variability at harvest and postharvest. Hyperspectral reflectance imaging has been previously used to detect sun stress and predict sunscald risk through a chlorophyll-carotenoid index (Cri; 430, 662, 454, 549 nm) on apples. The objective of this work was to adapt a non-destructive sorting index to standardize groups of fruit with predictive postharvest outcomes throughout the cold chain and treatments. d ‘Anjou pears were harvested from different canopy positions (internal, external, and random) in three commercial blocks during 2023. Hyperspectral images (640 x 840 px; 400–1100 nm) were captured from the exposed and unexposed sides of the fruit at harvest. The reflectance information was then extracted and pre-processed with Savizky-Golay and Standard Normal Variate filters. With this information, the Cri was calculated for every fruit. Cri values ranged from 0.9 to 3.6 for fruit from external canopy positions and 1.1 to 3.8 for those from internal ones. The analysis of variance showed significant differences in Cri values across fruit sides and tree positions (p < 0.01). These findings support the viability of using the chlorophyll-carotenoid index to sort pears with different sun stress levels at harvest. Further research is needed to evaluate the consistency in response of the different fruit groups when submitted to different cold chain scenarios and postharvest treatments.

Citramalate synthase is proposed to be the first committed step in the formation of branched chain esters in apples based on detailed biochemical, pharmacological, isotopic, and molecular data. However, the function of the full citramalate pathway, from the formation of citramalate to the formation of the branched chain esters containing 2-methylbutyl and 2-methylbutanoate moieties has not been tested using a gain of function model. In this work, we report on the transient transformation of ripening banana fruit with functional and non-functional alleles of MdCMS (MdCMS_1 and MdCMS_2, respectively) and report on the compounds induced by the addition of this gene. Banana do not produce appreciable levels of citramalate and make little to no 2-methylbutyl and 2-methylbutanoate containing esters. Following the transformation event, citramalate accumulated in banana transformed with MdCMS_1, but not MdCMS-2. Similarly, banana with the functional form of MdCMS produced modest levels of 2-methylbutyl acetate and 2-methylbutyl butanoate esters. Fruit transformed with MdCMS_1 also accumulated isoleucine as a by-product of the enhanced pathway throughput. Finally, there was a marked enhancement of propyl esters, likely a function of an increase in alpha-ketobutyrate, which is an intermediate in the citramalate pathway between citramalic acid and 2-methylbutyl and 2-methylebutnoate esters. The data provide the last necessary evidence for the conclusively documenting function of citramalate synthase as a functional pathway in apple useful for the production of aroma active branched-chain esters.